Rigorous derivation of a hyperbolic model for Taylor
dispersion
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Mikelic, A., & Duijn, van, C. J. (2009). Rigorous derivation of a hyperbolic model for Taylor dispersion. (CASA-report; Vol. 0936). Technische Universiteit Eindhoven.
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EINDHOVEN UNIVERSITY OF TECHNOLOGY Department of Mathematics and Computer Science
CASA-Report 09-36 November 2009
Rigorous derivation of a hyperbolic model for Taylor dispersion
by
A. Mikelić, C.J. van Duijn
Centre for Analysis, Scientific computing and Applications Department of Mathematics and Computer Science
Eindhoven University of Technology P.O. Box 513
5600 MB Eindhoven, The Netherlands ISSN: 0926-4507
Rigorous derivation of a hyperbolic model for
Taylor dispersion
Andro Mikeli´c ∗†
Universit´e de Lyon, Lyon, F-69003, FRANCE ; Universit´e Lyon 1, Institut Camille Jordan,
UMR 5208, UFR Math´ematiques, 43, Bd du 11 novembre 1918, 69622 Villeurbanne Cedex, France
C.J. van Duijn
Eindhoven University of Technology,
Department of Mathematics and Computer Sciences, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
October 13, 2009
Abstract
In this paper we upscale the classical convection-diffusion equa-tion in a narrow slit. We suppose that the transport parameters are such that we are in Taylor’s regime i.e. we deal with dominant P´eclet numbers. In contrast to the classical work of Taylor, we undertake a rigorous derivation of the upscaled hyperbolic dispersion equa-tion. Hyperbolic effective models were proposed by several authors and our goal is to confirm rigorously the effective equations derived by Balakotaiah et al in recent years using a formal Liapounov - Schmidt reduction. Our analysis uses the Laplace transform in time and an anisotropic singular perturbation technique, the small characteristic parameter ε being the ratio between the thickness and the longitudi-nal observation length. The P´eclet number is written as Cε−α, with α < 2. Hyperbolic effective model corresponds to a high P´eclet number close to the threshold value when Taylor’s regime turns to turbulent mixing and we characterize it by supposing 4/3 < α < 2. We prove
∗Research of A.M. was partially supported by the GNR MOMAS CNRS-2439 (Mod´elisation Math´ematique et Simulations num´eriques li´ees aux probl`emes de gestion des d´echets nucl´eaires) (PACEN/CNRS, ANDRA, BRGM, CEA, EDF, IRSN).
that the difference between the dimensionless physical concentration and the effective concentration, calculated using the hyperbolic up-scaled model, divided by ε2−α (the local P´eclet number) converges
strongly to zero in L2-norm. For P´eclet numbers considered in this
paper, the hyperbolic dispersion equation turns out to give a better approximation than the classical parabolic Taylor model.
Keywords Taylor’s dispersion; Goursat problem, large P´eclet num-ber; singular perturbation; Laplace’s transform; Danckwerts’ boundary conditions. AMS classcode 35B25; 76F25; 44A10
1
Introduction
Aim of this paper is to present an upscaled hyperbolic model for Taylor dispersion.
Dispersion expresses the deviation of a solute concentration with respect to its mean behavior. It is induced by the motion of a fluid that trans-ports the solute (molecular diffusion, convection and their interaction) or by chemical reactions.
Dispersion induced by a flow between two parallel plates (or through a tube) is classically modeled by an effective convection-diffusion equation of the type ∂c ∂t+ < v > ∂c ∂x = ˜Def f ∂2c ∂x2. (1)
Here < v > denotes the transversally averaged velocity and ˜Def f the
effec-tive dispersion coefficient.
The latter depends on the transversal P´eclet number PeT = < v > HD mol
, where Dmol is the molecular diffusivity and H vertical distance (tube
ra-dius). In his pioneering paper [29], Taylor found for tracer flow in a narrow tube that ˜Def f behaves as Dmol(1 + CPe2T). Here C is explicitly known, depending on the geometry. This expression for ˜Def f is believed to hold
until PeT reaches a threshold value. Crossing that value, turbulent mixing
appears and the dependence on PeT becomes either logarithmic, sublinear or linear (see [30] and chapter 9 from [17]).
In this work we study the dispersion between two parallel plates for P´eclet numbers in the Taylor regime, i.e. below the threshold value but nevertheless close to it. This in fact is the situation discussed in the classical Taylor paper [29].
In that paper, he considered the transport of a solute by Poiseuille flow in the presence of transversal (molecular) diffusion. The effective Taylor equation was derived for the cross-section averaged solute concentration. Taylor derived and experimentally verified, that for a cylindrical tube with radius H the effective equation reads
∂c ∂t+ < v > ∂c ∂x− Dmol ∂2c ∂x2 = − ∂JT ∂x , (2)
where the additional dispersion flux JT is given by
JT = −Def f∂x∂c = −H
2< v >2 48Dmol
∂c
∂x. (3)
This expression was formally justified by Aris in [3], using the method of spatial moments.
In this paper we present an alternative for the upscaled model in the Taylor regime which is of the form
∂c ∂t+ < v > ∂c ∂x+ < v > H2 48Dmol ∂2c ∂x∂t = 0. (4)
For reasons of simplicity we will derive the analogue of (4) in the setting of a Poiseuille flow between two parallel plates. Also the error estimates are done within this simplified setting.
There is a large number of papers related to Taylor dispersion, but only a few are concerned with a rigorous mathematical justification of the effective model. To guide the reader through the literature we present below a brief summary. We start by mentioning the center manifold approach of Mercer and Roberts [22] and the related paper [26] by Rosencrans. This approach allows one to calculate approximations at any order for the original Taylor model. Even though no error estimate was obtained, this approach gives a plausible argument for the validity of the effective model. A rigorous justification of the effective dispersion model including chemical reactions on the wall of the slit, was undertaken in [23] by Mikeli´c et al. An anisotropic singular perturbation technique was used and the results of this paper cover the classical Taylor case (1) and (2), as well.
Dispersion for reactive flows in tubes was studied by Paine et al. in [25]. They noted that the equation for the difference between the actual physi-cal and averaged concentrations is not closed, since it contains a dispersive source term. They used the ”single-point” closure schemes of turbulence modeling by Launder [19] to obtain a closed model for the averaged con-centration. We note that their effective equations contain non-local terms
depending on the solution. In fact the effective coefficients are not explicitly given.
The center manifold approach was applied to reactive flows by Balakota-iah and Chang in [4]. A number of effective models for different Damk¨ohler numbers were obtained, where the Damk¨ohler number is the ratio of the characteristic reaction time and the characteristic transversal diffusion time. In [15] by van Duijn et al, the case of general chemical reactions was consid-ered from the point of view of formal expansions with respect to the local P´eclet number, being the ratio between the characteristic longitudinal trans-port time and transversal diffusion time. Effective dispersion equations were obtained and the results were justified by numerical simulations, where the direct simulation of the physical multidimensional problem was compared to the solution of the effective dispersion equations. An excellent agreement was found. The expansion and numerical simulation results were justified at the level of mathematical rigor in the papers [12], [13], [23] and [24]. The analysis uses an anisotropic singular perturbation method to obtain error estimates for the approximations. At high P´eclet numbers the presence of the inlet boundaries required construction of boundary layers and this led to severe technical complications.
Characteristic to all these models is that they give rise to parabolic transport equations for the effective solute concentration.
Consequently, this leads to some non-physical properties:
i) In the starting equation the longitudinal diffusion is frequently ne-glected. Nevertheless, the dispersion equations have effective disper-sion in the longitudinal direction. Consequently, they predict infinite propagation speed of perturbations, which is (of course) not observed in experiments.
ii) For purely convective flows solute particles follows streamlines. Hence when flow reversal occurs the particules return to their original posi-tion. Obviously, this is not true anymore in the presence of transversal diffusion, since then particle move randomly in the transverse direction between streamlines. One speaks of partial reversibility if directly af-ter flow reversal a variance decrease is observed. On physical grounds one expects to have at least partial reversibility.
These reasons motivated Scheidegger [28] to propose already in 1958 the one-dimensional telegraph equation
∂2c ∂t2 + 1 τ ∂c ∂t = σ 2 v ∂2c ∂x2 (5)
as model for dispersion in porous media. Here σv is the velocity variance and τ a relaxation parameter.
For dispersion in a tube, Camacho developed in [8]–[10] upscaled hyper-bolic models. He used concepts from irreversible thermodynamics and he averaged the terms of the Fourier expansion of the solution in the original equation over the cross-section of the flow. In this way he arrived at the following non-Fickian relaxation equation for the Taylor flux JT:
∂JT ∂t + JT τ + (1 + β) < v > ∂JT ∂x −Dmol∂2JT ∂x2 = −σ2v ∂2c ∂x2. (6)
Here τ is again relaxation parameter time and β is a phenomenological coefficient. After some simplifications and manipulations, (6) leads to a fourth order equation for the averaged concentration:
∂c ∂t+ < v > ∂c ∂x− Dmol ∂2c ∂x2 + τef f ½ ∂2c ∂t2 + ¡ (< v > +βef f) < v > −σ2v ¢ ∂2c ∂x2 +(2 < v > +βef f) ∂ 2c ∂x∂t ¾ = τef f ½ 2Dmol ∂3c ∂x2∂t+ (2 < v > +βef f)Dmol ∂3c ∂x3 − D 2 mol ∂4c ∂x4 ¾ . (7) Here βef f and τef f are effective parameters related to β and τ . Neglecting molecular diffusion reduces (7) to the telegraph equation
τef f∂ 2c ∂t2 + ∂c ∂t+ < v > ∂c ∂x + τef f µ 2 < v > +βef f ¶ ∂2c ∂x∂t− τef f µ σ2v− (< v > +βef f) < v > ¶ ∂2c ∂x2 = 0. (8)
The results of Camacho were later extended to layered media by Berentsen et al in [7].
An alternative approach, based on a two-term Bubnov-Galerkin repre-sentation, was introduced by Khon’kin in [18]. For dispersion in a tube his calculations lead to a hyperbolic equation of the form
∂2c ∂t2+ 9 4 < v > ∂2c ∂x∂t+ 15 16 < v > 2 ∂2c ∂x2+ 15Dmol H2 ¡ ∂c ∂t+ < v > ∂c ∂x ¢ = 0. (9) Yet another approach, similar but more systematic, was developed by Bal-akotaiah et al. in [5], [6] and [11]. They use the Liapounov-Schmidt reduc-tion together with a perturbareduc-tion argument. In the framework of Taylor’s
paper they obtained the dispersion equation ∂c ∂t+ < v > ∂c ∂x+ < v > H2 48Dmol ∂2c ∂x∂t = Dmol ∂2c ∂x2. (10) Since Dmol is very small, the right hand side could be disregarded. In this approximation equation (10) reduces to our equation (4). In this hyper-bolic limit, equation (10) does not suffer from default i) and has partial reversibility.
In this paper we address the rigorous mathematical justification of the formal results and observations made by Balakotaiah and coauthors in the papers [5], [6] and [11]. We will undertake a different derivation of the effective model, following the expansions proposed in [15]. It gives equation (4), as a rigorous result.
The plan of the paper is as follows. In Section 2 we give the precise setting of the problem and derive its dimensionless form. Then we present the effective problem in its dimensionless form and the main results of the paper. Finally, the effective dispersion problem in its full dimensional form is presented. In Section 3 we recall some facts about the vector-valued Laplace transform and give the Laplace transform of our problem. It permits us to get precise estimates on the transformed solution.
In Subsection 4.1 we present the formal derivation of the hyperbolic effective problem. Even though our approach is different from the one pro-posed by Balakatoiah et al in [5], [6] and [11], we obtain the same effective dispersion model. In Subsection 4.2 existence, uniqueness and estimates explicit in ε for the solution to the effective problem are obtained. These estimates are used in Section 5 to prove weak convergence. In Section 6 we add a boundary layer at the inflow boundary. This allows us to prove strong convergence .
For P´eclet numbers close to the threshold value, we are able to obtain a better approximation with hyperbolic effective equation (4) than with the parabolic model (2)- (3). The latter was rigorously justified in [24]. In that paper we needed boundary layer corrections, which complicated the analysis enormously. In the present approach these mathematical technical problems are avoided. Therefore in conclusion: effective equation (4) is a better approximation in the mathematical sense (in the sense of estimates) and easier to justify.
2
Setting of the problem and main result
To fix ideas, we give the precise setting of the problem. We consider the transport of a solute by diffusion and convection by Poiseuille’s velocity in a semi-infinite two-dimensional channel. The solute particles do not react among themselves nor with the walls. Therefore we suppose zero flux condi-tions at the lateral walls. The case when the solute undergoes an adsorption process at the lateral boundary will be considered in a forthcoming paper.
We consider the following model for the solute concentration c∗:
a) transport through channel Ω∗= {(x∗, y∗) : 0 < x∗< +∞, |y∗| < H}
∂c∗ ∂t∗ + V (y∗) ∂c∗ ∂x∗ − Dmol ∂2c∗ ∂(x∗)2 − Dmol ∂2c∗ ∂(y∗)2 = 0 in Ω∗, (11) where V (z) = Q∗(1−(y∗/H)2) and where Q∗(velocity) and Dmol(molecular
diffusion) are positive constants.
b) zero flux at channel wall Γ∗ = {(x∗, y∗) : 0 < x∗ < +∞, |y∗| = H}
−Dmol∂y∗c∗ = 0 on Γ∗, (12)
c) infiltration with a pulse of water containing a solute of concentration c∗f, followed by solute-free water is stated using the Danckwerts boundary con-dition from [16] −Dmol∂x∗c∗+ V (y∗)c∗ = ½ V (y∗)c∗f, for 0 < t∗ < t∗0 0, for t > t∗ 0. (13) For problems posed on finite interval, we will replace Ω∗ by Ω∗
L= {(x∗, y∗) :
0 < x∗ < L, |y∗| < H} and Γ∗ by Γ∗L = {(x∗, y∗) : 0 < x∗ < L, |y∗| = H} in (11), (12). In such setting, at x∗ = L we impose the following boundary
condition
−Dmol∂x∗c∗ = 0 on x∗ = L, y ∈ (0, H). (14)
The natural way of analyzing this problem is to introduce appropriate scales. This requires characteristic or reference values for the parameters in variables involved. The obvious transversal length scale is H. For all other quantities we use reference values denoted by the subscript R. Setting
c = c ∗ ˆc, x = x∗ LR, y = y∗ H, t = t∗ TR, Q ∗ = Q R, Dmol= DR, (15)
where LRis the ” observation distance ”, we obtain the dimensionless
equa-tions ∂c ∂t+ Q∗TR LR (1 − y 2)∂c ∂x− D∗TR L2 R ∂2c ∂x2 − D∗TR H2 ∂2c ∂y2 = 0 in Ω (16)
and −D ∗T R H2 ∂c ∂y = 0 on Γ, (17) where Ω = (0, +∞) × (−1, 1) and Γ = (0, +∞) × {−1, 1}. (18) The problem involves the following time scales:
TL = characteristic longitudinal time scale = LQR∗,
TT = characteristic transversal time scale = H2 D∗,
and the dimensionless number Pe = LRQ∗
Dmol (P´eclet number). In this paper we fix the reference time by setting TR = TL. We are going to investigate
the behavior of the two-dimensional system (16)-(17) with respect to the small parameter ε = H
LR.
To carry out the analysis we need to compare the dimensionless numbers with respect to ε. For this purpose we set Pe = Pe0ε−α. Introducing the dimensionless numbers in equations (16)-(17) yields the problem:
Pe0 ¡ ∂cε ∂t + (1 − y 2)∂cε ∂x ¢ = εα∂ 2cε ∂x2 + εα−2 ∂2cε ∂y2 in Ω+× (0, T ), (19) −εα−2∂cε ∂y = 0 on Γ +× (0, T ), (20) cε(x, y, 0) = c0(x, y) for (x, y) ∈ Ω+, (21) − εα Pe0 ∂xcε+ (1 − y2)cε= ½ (1 − y2)c f(t), for 0 < t < t0 0, for t > t0. at {x = 0}, (22) ∂cε ∂y(x, 0, t) = 0, for (x, t) ∈ (0, +∞) × (0, T ). (23) The latter condition results from the y−symmetry of the solution. Further
Ω+= (0, +∞) × (0, 1), Γ+= (0, +∞) × {1}, and T is an arbitrary chosen positive number.
We study the behavior of this problem as ε & 0, while keeping Pe 0 of order O(1). We are only interested in the case 2 > α > 1 which leads to dominant hyperbolic behavior. Note that Taylor’s data from [29] correspond
to α = 1.7 and α = 1.9. We refer to [15] for detailed discussion about data, expansions and simulations.
Specifically, as in [23], [24], [12] and [13], we will derive expressions for the effective values of the dispersion coefficient and velocity, and an effective one dimensional dispersion equation for small values of ε. The main difference is that here the effective equation will be hyperbolic.
In this paper we suppose c0= c0(x) and prove that the correct upscaling of the Laplace transform of the problem (19)-(23) gives the following effective problem: τ c0+ < v > ∂xc0− mε2−αPe0τ ∂xc0= F in (0, +∞), (24) F = Z 1 0 c0(x, y) dy − mε2−αPe0∂x Z 1 0 c0(x, y) dy. (25) c0|x=0 = ˆcf −Pe0mε 2−α(c 0|x=0− τ ˆcf) < v > −τ Pe0mε2−α , (26) where < v >=R01v(y)dy = 23, m =< v(y)P4(y) >= −3154 , cf = 0 for t > t0 and P4(y) = 32(y 2 6 − y4 12 − 7
180) is the solution for −∂yyP4(y) = −v(y)− < v >< v > on (0, 1), ∂yP4 = 0 on y = 0 and − ∂yP4 = 0 on y = 1 R1 0 P4(y) dy = 0. (27)
Remark 1. Derivation of the ODE (24) is given in details in subsection 4.1. Obtaining of the effective boundary conditions at the inlet boundary x = 0, is independent of the inner expansion developed in 4.1 and leading to the effective PDE.
Let us give a formal derivation of the boundary condition (26): We sup-pose that c0|x=0 = ˆcf + ε2−αcf 1. then the corresponding correction term at
x = 0 is of the form −v(y) Pe0cf 1− v(y)P4(y) ¡ c0(0) − τ (ˆcf+ ε2−αcf 1) ¢ = −v(y) ½ (P4(y) −< v >m )(c0(0) − τ ˆcf − ε2−ατ cf 1)+ ( 1 Pe0 − m < v >ε 2−ατ )c f 1+ m < v >(c0(0) − τ ˆcf) ¾ .
The above expression has zero mean if and only if cf 1 is chosen as cf 1= −Pe0m(c0|x=0− τ ˆcf)
< v > −τ Pe0mε2−α.
After inverting the Laplace transform and supposing that c0(0) = cf(0),
we get the following one dimensional Goursat’s problem for the dimension-less effective concentration cef f:
(EF F ) ∂tcef f+ < v > ∂xcef f − mPe0ε2−α∂ 2cef f ∂x∂t = 0 for (x, t) ∈ R 2 +, cef f|x=0 = cf(t) − Z t 0 e<v>(t−z))/(Pe0mε2−α)∂zcf dz, ∂xcef f ∈ L2((0, +∞) × (0, T )), cef f|t=0= c0(x), Let us announce our main result.
Theorem 1. Let 2 > α > 4/3, let c0 ∈ H2(R+) and let cf ∈ C∞[0, T ]. Let
cef f be given by (EFF) and let c0 be its Laplace transform given by (24)-(26). Then we have
εα−2
Pe0
(ˆcε− c0) − P4(y)(< c0 > −τ c0) * 0 weakly in L2(Ω+), as ε → 0, ∀τ ∈ C, <τ > 0, (28) where ˆcε is the Laplace transform of cε.
Let us suppose in addition cf(0) = c0(0). Then the above convergence takes place in H2(C
+; L2(Ω+)) and for all T ∈ (0, +∞) we have εα−2 Pe0 (c ε− cef f) + P 4(y)∂c ef f ∂t * 0 weakly in L 2(Ω+× (0, T )), as ε → 0. (29) Our result could be restated in dimensional form:
Corollary 1. Let us suppose that LR>> max{Dmol/Q∗, Q∗H2/D
mol, H}.
Then the upscaled dimensional approximation for (11) reads ∂c∗,ef f ∂t∗ + < V > ∂c∗,ef f ∂x∗ − mHPeT ∂2c∗,ef f ∂x∗∂t∗ = 0, in R+× (0, T ), (30) c∗,ef f|t=0= c0(x), (31) c∗,ef f|x=0 = c∗f(t∗) − Z t∗ 0 e(<V >(t∗−z∗))/(PeTmH)∂ z∗c∗f(z∗) dz∗, (32)
where PeT = Q ∗H
Dmol is the transversal P´eclet number, < V >=
1 H
Z H 0
V (y) dy and H PeT is the mixing length.
Remark 2. At this point it is good to note that equation (30) describes the effective model. However, its solution c∗,ef f is only the zeroth order term in asymptotic expansion (46). In order to have the higher order approximation, it is necessary to use c∗,approx(x∗, y∗, t∗) = c∗,ef f(x∗, t∗) −∂c ∗,ef f ∂t∗ (x∗, t∗) H2 DmolP4( y∗ H) (33) Finally, with little more work we have the following strong convergence result
Theorem 2. Let 2 > α > 4/3, let c0 ∈ H2(R+) and let cf ∈ C∞[0, T ]. Let
cef f be given by (EFF) and let c0 be its Laplace transform given by (24)-(26). Then we have εα−2 Pe0(ˆc ε− c0) − P 4(y)(< c0> −τ c0) → 0 in L2(Ω+), as ε → 0, ∀τ ∈ C, <τ > 0, (34) where ˆcε is the Laplace transform of cε.
Let us suppose in addition cf(0) = c0(0). Then the above convergence takes place in H2(C
+; L2(Ω+)) and for all T ∈ (0, +∞) we have εα−2 Pe0(c ε− cef f) + P 4(y)∂c ef f ∂t → 0 in L 2(Ω+× (0, T )), as ε → 0. (35) Remark 3. We note that previous results apply to the case of problem (11)-(13) posed for x ∈ (0, L) and with the outlet boundary condition (14). The statements of the results and the proofs are identical.
3
Vector valued Laplace transform and
applica-tions to PDEs
We start this section by recalling the basic facts about applications of Laplace’s transform to linear parabolic equations. The Laplace’s transform method is widely used in solving engineering problems. In applications it is usually called the operational calculus or Heaviside’s method.
For locally integrable function f ∈ L1
loc(R) such that f (t) = 0 for t < 0
and |f (t)| ≤ Aeat as t → +∞, the Laplace transform of f , denoted ˆf , is defined as ˆ f (τ ) = Z +∞ 0 f (t)e−τ t dt, τ = ξ + i η ∈ C. (36) It is closely linked with Fourier’s transform in R. We note that
ˆ
f (τ ) = F¡f (t)e−ξt¢(−η), ξ > a, (37) where the Fourier’s transform of a function g ∈ L1(R) is given by
F¡g(t)¢(ω) = Z
R
g(t)eiωt dt, ω ∈ R.
It is well-known (see e.g. [31] or [14]) that ˆf defined by (36) is analytic in the half-plane {Re(τ ) = ξ > a} and it tends to zero as Re(τ ) → +∞.
For real applications, Laplace’s transform of functions is not well-adapted and it is natural to use Laplace’s transform of distributions. It is defined for distributions with support on [a, +∞) i.e. for f ∈ D0
+(a), where D+0 (a) = {f ∈ D0(R); supp f ⊂ [a, +∞)}. If S0(R) denotes the space of distributions
of slow growth, then we introduce S0
+(R) by
S+0 (R) = D0+(0) ∩ S0(R) (38) and we use the formula (37) to define Laplace’s transform for f ∈ D0+(a) such that f e−ξt∈ S0
+(R) for all ξ > a. This approach permits the rigorous operational calculus. For details we refer to classical textbooks as [31] by Vladimirov.
Laplace’s transform is applier to linear ODEs and PDEs, the transform problem is solved and its solution ˆf is calculated. Then the important question is how to inverse the Laplace’s transform. First we need a suitable space for image functions. It is the algebra H(a) defined by
H(a) = {g ∈ Hol¡{τ ∈ C; Re(τ ) > a}¢satisfying the growth condition : for any σo> a there are real numbers C(σo) > 0 and
m = m(σo) ≥ 0such that |g(τ )| ≤ C(σo) (1 + |τ |m), Re(τ ) > σo}.
(39) For elements of H(a) we have the following classical result.
Theorem 3. ([31] pp. 162-165) Let ˆf ∈ H(a) be absolutely integrable with respect to η on R for certain ξ > a. Then the following formula holds true.
f (t) = 1 2πi Z ξ+i∞ ξ−i∞ ˆ f (z)ezt dz. (40)
These classical results are not sufficient for our purposes. We need results for reflexive Sobolev space X valued Laplace’s transform. Furthermore we need an inversion theorem in Lp((0, +∞); X). The corresponding theory
could be found in Arendt [2] and we give only results directly linked to our needs. For a reflexive Banach space X we set
Cw∞(R+; X) = {r ∈ C∞((0, +∞); X); krkw = sup n∈N sup λ>0 λn+1 n! ° ° dn dλnr(λ) ° ° X < +∞}. (41) Then we have the following result.
Theorem 4. ([2], Chapter 2) Let X be a reflexive Banach space. Then the (real) Laplace’s transform f 7→ ˆf is an isometric isomorphism between L∞(R
+; X) and Cw∞(R+; X).
Let X be a Hilbert space, C+= {λ ∈ C : Re λ > 0} and let H2(C+, X) be the subset of the space of holomorphic functions defined by
H2(C+, X) = { h : C+→ X such that ||h||H2(C+,X)= sup x>0
Z R
||h(x+is)||2X ds < +∞}. Then we have
Theorem 5. (vector valued Paley-Wiener theorem from [2], page 48) Let X be a Hilbert space. Then the map f → ˆf |C is an isometric isomorphism of L2(R
+, X) onto H2(C+, X).
In our situation, we have to deal with C+replaced by {λ ∈ C : Re λ > τ0 > 0}. But this means just replacing f by e−τ tf in Theorem 5. Other, more direct way to proceed is to follow ideas from [14] and use a direct approach based on the link to Fourier’s transform. We apply this result in the study of the upscaled equations and then in the error estimates. We derive estimates for the solutions of the Laplace transformed problem.
4
Rigorous derivation and analysis of the effective
problem
4.1 Formal asymptotic expansion
We suppose α ≥ 1.
Let the operator Lε be given by
Lεζ = τ ζ + (1 − y2)∂ζ ∂x− εα Pe0 µ ∂2ζ ∂x2 + ε−2 ∂2ζ ∂y2 ¶ . (42)
The dimensionless physical concentration cε satisfies (19)-(23). Its Laplace
transform ˆcε is thus solution of
Lεˆcε= c0 in (0, +∞) × (0, 1) (43) − εα Pe0∂xˆc ε+ (1 − y2)ˆcε= (1 − y2)ˆc f, for (x, y) ∈ {0} × (0, 1), (44) −εα−2 Pe0 ∂yˆcε(x, y, τ ) = 0 on (0, +∞) × ({0} ∪ {1}). (45) We start from the system (43)-(45) and search for ˆcε in the form
ˆcε= c0(x, t; ε) + ε2−αc1(x, y, t) + ε2(2−α)c2(x, y, t) + . . . (46) After introducing (46) into the equation (43) we get
ε0 n τ c0+ (1 − y2)∂xc0− 1 Pe0 ∂yyc1− c0 o + ε2−α n τ c1+ (1 − y2)∂xc1− −Pe1 0∂yyc 2o= O(ε2(2−α)) + O(εα). (47)
In order to have (47) for every ε ∈ (0, ε0), all coefficients in front of the powers of ε should be zero.
The problem corresponding to the order ε0 is − 1 Pe0∂yyc 1= −(1/3 − y2)∂ xc0+ c0− Z 1 0 c0(x, y) dy −¡τ c0+ 2∂xc0/3 − Z 1 0 c0(x, y) dy ¢ on (0, 1), ∂yc1 = 0 on y = 0 and − ∂yc1= 0 on y = 1 (48)
for every x ∈ (0, +∞). By Fredholm’s alternative, the problem (48) has a solution if and only if
τ c0+ 2∂xc0/3 −
Z 1 0
c0(x, y) dy = 0 in (0, +∞). (49) For α close to 2, the equation (49) gives a coarse approximation and it does not suit our needs. It is interesting to include some higher order terms and get better approximation. We proceed as in [23] and [15], following an idea from [27], and suppose that
τ c0+ 2∂xc0/3 − Z 1
0
The hypothesis (50) will be justified a posteriori, after getting an equation for c0. It is convenient to use (50) and write the right hand side of the first equation in (48) as −(1/3 − y2)∂xc0− ¡ τ c0+ 2∂xc0/3 − Z 1 0 c0(x, y) dy ¢ = −3 2( 1 3 − y 2)( Z 1 0 c0(x, y) dy − τ c0) + O(ε2−α) in (0, +∞). (51) Let π(x, y),R01π(x, y) dy = 0, be the unique solution to the problem
−∂yyπ = c0(x, y) − Z 1 0 c0(x, y) dy on (0, 1), ∂yπ|y=0,1= 0. (52) Then (48) reduces to − 1 Pe0 ∂yyc1 = −3 2(1/3 − y 2)( Z 1 0 c0(x, y) dy − τ c0) +c0(x, y) − R1 0 c0(x, y) dy on (0, 1), ∂yc1 = 0 on y = 0 and − ∂ yc1 = 0 on y = 1 (53)
for every x ∈ (0, +∞), and we have 1 Pe0c 1(x, y, t) = 3 2( y2 6 − y4 12− 7 180)( Z 1 0 c0(x, y) dy − τ c0) + π(x, y) + C0(x, t), (54) where C0 is an arbitrary function.
Let us go to the next order. Then we have − 1 Pe0∂yyc 2 = −(1 − y2)∂ xc1− τ c1− εα−2 ¡ τ c0+ 2∂xc0/3− R1 0 c0(x, y) dy ¢ on (0, 1), ∂yc2 = 0 on y = 0 and − ∂ yc2 = 0 on y = 1 (55)
for every x ∈ (0, +∞). The problem (55) has a solution if and only if τ c0+ 2∂xc0/3 − Z 1 0 c0(x, y) dy + ε2−α∂x( Z 1 0 (1 − y2)c1 dy)+ ε2−ατ ( Z 1 0 c1 dy) − ε2 Pe0∂xx( Z 1 0 c1dy) = 0 in (0, +∞). (56)
(56) is the equation for c0. Obviously, c0+ε2−α
Pe0 C0satisfies the same equation at order O(ε2(2−α)) and we choose C
0 = 0 without loosing generality. Finally, after straightforward calculations, the equation (56) becomes (24)-(25), with slightly more general F given by
F = Z 1 0 c0(x, y) dy +ε2−αPe0∂x¡ 4315 Z 1 0 c0(x, y) dy − Z 1 0 (1−y2)π(x, y) dy¢. (57)
4.2 Study of the upscaled diffusion-convection equation on the half-line
In Section 5, we will prove that the original problem can be approximated by an upscaled one dimensional diffusion-convection equation. The present section is thus devoted to the study of this type of equation in the half-line. The results of Subsection 4.2 are used in Section 5.
For ¯Q, ¯D and γ > 0, we consider the problem ∂tu + ¯Q∂xu + γ ¯D∂xtu = G in (0, +∞) × (0, T ), ∂xu ∈ L2((0, +∞) × (0, T )), u(x, 0) = u0 in (0, +∞), u = cf at x = 0. (58)
Let Ωl = R+× {Re(τ ) > 0}. After applying the Laplace transform with respect to the time variable we get the following equation for the Laplace transform ˆu(x, τ ) of u: τ ˆu + ¯Q∂xu + γ ¯ˆ Dτ ∂xu = ¯ˆ F + γU0 = ˆG + u0(x) + γ ¯D∂xu0 in Ωl, ∂xu ∈ Lˆ 2(R+), Re(τ ) > 0, ˆ u = ˆcf at x = 0, (59) where τ = ξ + i η ∈ C, ξ > 0. In order to capture correctly the decay in τ , we transform the problem (59) into the following problem for the unknown ˆ v = ˆu − u0 β + τ, β > 0, τ ˆv + ¯Q∂xˆv + γ ¯Dτ ∂xv = ˆˆ G +βu0β + τ− ¯Q∂xu0 + γ ¯Dβ∂β + τxu0 in Ωl, ∂xv ∈ Lˆ 2(R+), Re(τ ) > 0, ˆ u = ˆcf −β + τu0 at x = 0. (60)
We decompose ˆv as ˆv = ˆa + γ ¯Dβ+τβ f , withˆ
τ ˆa + ¯Q∂xˆa + γ ¯Dτ ∂xˆa = ˆG + βu0β + τ− ¯Q∂xu0 in Ωl,
∂xˆa ∈ L2(R +), Re(τ ) > 0, ˆa = ˆcf− β + τu0 at x = 0, (61) and τ ˆf + ¯Q∂xf + γ ¯ˆ Dτ ∂xf = ∂ˆ xu0 in Ωl, ∂xf ∈ Lˆ 2(R+), Re(τ ) > 0, ˆ f = 0 at x = 0. (62)
For the sake of simplicity, we write
`(τ ) = ¯Q + γτ ¯D, Re(τ ) = ξ > 0. We have for ξ > 0 Re³ τ l(τ ) ´ = Re³ τl(τ) |l(τ )|2 ´ = ξ ¯Q + γ ¯D|τ |2 (γ ¯D)2|τ |2+ ¯Q2+ 2γ ¯D ¯Qξ > 0, (63) 1/Re³ τ l(τ ) ´ = γ ¯D + ¯Q Q + γ ¯¯ Dξ γ ¯D|τ |2+ ¯Qξ, (64) 1 |`(τ )| = 1 p ¯ Q2+ (γ ¯D)2|τ |2 ≤ √ 2 ¯ Q + γ ¯D|τ |. (65) Problem (61) for ˆa allows the following explicit solution:
ˆa(x, τ ) = (ˆcf(τ ) −β + τu0 |x=0)e−τ x/`(τ )+ Z x 0 e−τ (x−z)/`(τ )G(z, τ )ˆ `(τ ) dz + Z x 0 βu0(x − z) − ¯Q∂xu0(x − z) (β + τ )`(τ ) e −τ z/`(τ )dz; (66) ∂xˆa(x, τ ) = `(τ )1 (u0|x=0− τ ˆcf(τ ) − ¯ Q∂xu0|x=0 β + τ )e −τ x/`(τ )+ Z x 0 β∂xu0(x − z) − ¯Q∂xxu0(x − z) (β + τ )`(τ ) e −τ z/`(τ ) dz − Z x 0 e−τ (x−z)/`(τ )τ ˆG(z, τ ) `2(τ ) dz; (67)
Problem (62) for ˆf allows the following explicit solution: ˆ f (x, τ ) = Z x 0 e−τ (x−z)/`(τ )∂xu0(z, τ ) `(τ ) dz; (68) ∂xf (x, τ ) = −ˆ τ ∂xu0(x) `2(τ ) − Z x 0 τ ∂xu0(z) `2(τ ) e −τ (x−z)/`(τ ) dz. (69)
This explicit formula allows us to find the exact behavior of u with respect to γ.
We now aim to give explicit estimates with respect to τ for ˆu in Hp((0, +∞)).
First, for any p ∈ [1, +∞], Young’s inequality implies that kˆu(·, τ )kLp(R +)≤ C µ |ˆcf| +||u0||H1(R+) |τ | + || ˆG(·, τ )||L2(0,+∞) ¶ (70) Estimating ∂xu is more delicate. We start by estimating the terms in theˆ
equalities (67) and (69) concentrated at the boundary. Using (63)-(65) we get the following estimate:
|| 1 `(τ )(u0|x=0− τ ˆcf(τ ) − ¯ Q∂xu0|x=0 β + τ )e −τ x/`(τ )− γ ¯D β β + τ τ ∂xu0(x) `2(τ ) kLp(R+)≤ C n |u0|x=0− cf(0)| + |τ ˆcf − cf(0)| +|∂xu|τ |0|x=0|+ ||∂xu0||L2(R+) |τ | o . (71) Next we estimate the convolution terms using Young’s inequality and (63)-(65): || Z x 0 β∂xu0(x − z) − ¯Q∂xxu0(x − z) (β + τ )`(τ ) e −τ z/`(τ ) dz − Z x 0 e−τ (x−z)/`(τ )τ ˆG(z, τ ) `2(τ ) dz||Lp(R+)≤ C n ||τ ˆG(·, τ )||L2(R+)+ ||∂xu0||H1(R+) |τ | o (72) ||γ ¯D β β + τ Z x 0 τ ∂xu0(z) `2(τ ) e −τ (x−z)/`(τ ) dz|| Lp(R+)≤ C ||∂xu0||L2(R+) |τ | . (73) The following estimates are then straightforward:
Lemma 1. Let
Then the problem (59) has a unique solution ˆu ∈ L2(R +; H1(R+)) satisfying (70) and k∂xu(·, τ )kˆ Lp((0,+∞))≤ C n |u0|x=0− cf(0)| + |τ ˆcf− cf(0)| + ||∂xu0||L2(R+) |τ | +||τ ˆG(·, τ )||L2(R+)+ ||∂xu0||H1(R+) |τ | o , (75)
with τ = ξ + i η, ξ > 0 and p ∈ [1, +∞]. Constant C does not depend on γ. Let in addition to (74) the data satisfy the compatibility condition u0(0) = cf(0). Then the problem (58) has a unique solution u ∈ H1(R2+) satisfying
k∂xukL2(R2 +)= k∂xukˆ H2(C+,L2((0,+∞)) ≤ C n ||cf||H1(R+)+ ||G||H1(R+)+ ||u0||H2(R+) o . (76)
Next we estimate the expression τ ˆu − u0. We have τ ˆu − u0 = τ ˆv −τ +ββu0. As before ˆv is decomposed as ˆv = ˆa + γ ¯Dβ
τ + βf , where ˆa is given by (61) andˆ ˆ
f by (62). Direct calculation gives τ ˆa(x, τ ) = (ˆcf(τ ) − u0|x=0+ ¯ Q∂xu0 β + τ |x=0)e −τ x/`(τ )+ Z x 0 e−τ (x−z)/`(τ )τ ˆG(z, τ ) `(τ ) dz + Z x 0 β∂xu0(x − z) − ¯Q∂xxu0(x − z) (β + τ ) e −τ z/`(τ ) dz + βu0(x) − ¯Q∂xu0(x) τ + β ; (77) τ ∂xˆa(x, τ ) = `(τ )τ (u0|x=0− τ ˆcf(τ ) − ¯ Q∂xu0|x=0 β + τ )e −τ x/`(τ )+τ ˆG(x, τ ) `(τ ) − Z x 0 β∂xu0(x − z) − ¯Q∂xxu0(x − z) β + τ e −τ z/`(τ ) dz − Z x 0 e−τ (x−z)/`(τ )τ2G(z, τ )ˆ `2(τ ) dz +β∂xu0(x) − ¯Q∂xxu0(x) τ + β + β∂xu0|x=0− ¯Q∂xxu0|x=0 τ + β e −τ x/`(τ ). (78)
For the second component ˆf we have τ ˆf (x, τ ) = − Z x 0 e−τ z/`(τ )∂xxu0(x − z, τ ) dz + ∂xu0(x) −e−τ x/`(τ )∂xu0|x=0; (79) τ ∂xf (x, τ ) = −ˆ Z x 0 e−τ z/`(τ )∂xxxu0(x − z, τ ) dz + ∂xxu0(x) + τ `(τ )e −τ x/`(τ )∂ xu0|x=0. (80)
Equalities (77) and (79) imply the following result
Lemma 2. Let us suppose the assumption (74)on the data. Then, as in Lemma 1 the problem (59) has a unique solution ˆu ∈ L2(R+; H1(R+)) sat-isfying (70), (75) and ku0− τ ˆukLp((0,+∞)) ≤ C n |u0|x=0− cf(0)| + |τ ˆcf − cf(0)| + ||∂xu0||H1(R+) |τ | +||τ ˆG(·, τ )||L2(R+)+ ||∂xu0||H1(R+) |τ | o , (81)
with τ = ξ + i η, ξ > 0 and any p ∈ [1, +∞]. Constant C does not depend on γ
Let in addition to (74) the data satisfy the compatibility condition u0(0) = cf(0). Then the problem (58) has a unique solution u ∈ H1(R2
+) satisfying (76) and k∂tukL2(R2 +)= ku0− τ ˆukH2(C+,L2((0,+∞)) ≤ C n ||cf||H1(R+)+ ||G||H1(R+)+ ||u0||H2(R+) o . (82)
It remains to study the limit γ → 0. Let uγ = u be given by (58). Let
uγ0 satisfies (58) with γ = 0. Then we have
ˆ
uγ(x, τ ) = ˆu(x, τ ) → ˆuγ0(x, τ ), ∀x ∈ R+ and ∀τ ∈ C+, (83) u0− τ ˆuγ(x, τ ) = u0− τ ˆu(x, τ ) → u0− τ ˆuγ0(x, τ ), ∀x ∈ R+ and ∀τ ∈ C+,
(84) ∂xuˆγ(x, τ ) = ∂xu(x, τ ) → ∂ˆ xuˆγ0(x, τ ), ∀x ∈ R+ and ∀τ ∈ C+. (85) Next, under the hypothesis (74) and with the compatibility condition u0(0) = cf(0), Lemmas 1 and 2 are valid and sequences |ˆuγ|2, |u0−τ ˆuγ|2 and |∂xuˆγ|2
are bounded from above by a non-negative function integrable with respect to x and η = Im τ and bounded with respect to ξ = <τ . Consequently, Lebesgue’s dominated convergence theorem gives
Lemma 3. Let us suppose the assumption (74)on the data and let, fur-thermore, the data satisfy the compatibility condition u0(0) = cf(0). Let
uγ = u ∈ H1(R2+) be the unique solution for the problem (58), satisfying estimates (76) and (82). Let uγ0 ∈ H1(R2+) be the unique solution for the problem (58) with γ = 0. Then we have
ˆ uγ→ ˆuγ0, u0− τ ˆuγ→ u0− τ ˆuγ0 and ∂xuˆγ → ∂xuˆγ0 in H2(C+, L2((0, +∞)), as γ → 0, (86) uγ→ uγ0, ∂tuγ → ∂tuγ0and ∂xuγ → ∂xuγ0in L2(R2+), as γ → 0. (87)
5
Proof of Theorem 1
STEP 1Let H1(Ω+) be the usual Sobolev space, but complex valued. Let v(y) = 1 − y2 and c
0(x, y) = c0(x) =< c0>. We write the problem (43)-(45) in the variational form Z Ω+τ ˆc εϕ dxdy + Z Ω+v(y)∂xˆc εϕ dxdy + εα Pe0 Z Ω+(∂xˆc ε∂ xϕ + ε−2∂yˆcε∂yϕ) dxdy + Z 1 0 v(y)ˆcε|x=0ϕ|x=0 dy = Z Ω+c0ϕ dxdy + Z 1 0 v(y)ˆcfϕ|x=0 dy, ∀ ϕ ∈ H1(Ω+), ∀τ ∈ C+. (88) Next let P4(y) = 3
2(y 2 6 −y 4 12−1807 ) and m = R1 0 v(y)P4(y) dy =< vP4>=
−4/315. We write the problem (24)-(26) in the variational form Z Ω+τ c 0ϕ dxdy + Z Ω+v(y)∂xc 0ϕ dxdy + εα Pe0 Z Ω+(∂xc 0∂ xϕ + ε−2∂yc0∂yϕ) dxdy + Z 1 0 v(y)c0|x=0ϕ|x=0 dy = Z Ω+ c0ϕ dxdy + Z 1 0 v(y)ˆcfϕ|x=0 dy− Z Ω+ mε2−αPe0∂x< c0> ϕ dxdy + ε α Pe0 Z Ω+ ∂xc0∂xϕ dxdy+ Z Ω+ (v(y)− < v >)∂xc0ϕ dxdy + Z Ω+ ε2−αPe0mτ ∂xc0ϕ dxdy− Z 1 0 v(y)Pe0mε2−α(c0|x=0− τ ˆcf) < v > −Pe0mτ ε2−α ϕ|x=0 dy, ∀ ϕ ∈ H1(Ω+), ∀τ ∈ C+. (89) It should be noticed that the equation (24) is the first order partial differ-ential equation in x and the 3rd and the 4th term at the left hand side of (89) are added to allow the comparaison with (88). They do not come from integration by parts and the test functions do not have to satisfy the boundary condition at x = 0.
Then the function qε = εα−2(ˆcε− c0)/Pe0 satisfies the following varia-tional equation b(qε, ¯ϕ) = Z Ω+τ q εϕ dxdy + Z 1 0 v(y)qε|x=0ϕ|x=0 dy + Z Ω+v(y)∂xq εϕ dxdy+ εα Pe0 Z Ω+ (∂xqε∂xϕ + ε−2∂yqε∂yϕ) dxdy = εα−2 Z Ω+ < v > −v(y) Pe0 ∂xc 0ϕ dxdy − Z Ω+mτ ∂xc 0ϕ dxdy + Z Ω+m∂xc0ϕ dxdy − ε2(α−1) Pe20 Z Ω+∂xc 0∂ xϕ dxdy+ Z 1 0 v(y) m(c0|x=0− τ ˆcf) < v > −Pe0mτ ε2−α ϕ|x=0 dy, ∀ ϕ ∈ H1(Ω+), ∀τ ∈ C+. (90) STEP 2
Then using the results from Sections 4.1-4.2, we have |εα−2 Z Ω+ v(y)− < v > Pe0 ∂xc 0q¯ε dxdy| ≤ |εα/2−1 Z Ω+ ∂yP4 Pe0 ∂xc 0εα/2−1∂ yq¯ε dxdy| ≤ Cεα/2−1||∂xc0||L2(Ω+)||εα/2−1∂yq¯ε||L2(Ω+) (91) | Z Ω+ Pe0mτ ∂xc0q¯ε dxdy| ≤ C|τ |||∂xc0||L2(Ω+)||¯qε||L2(Ω+) (92) | Z Ω+ Pe0∂xm < c0 > +¯qε dxdy| ≤ C||c0||H1(Ω+)||¯qε||L2(Ω+) (93) ε2(α−1) Pe2 0 | Z Ω+ ∂xc0∂xq¯ε dxdy| ≤ Cε3α/2−2||∂xc0||L2(Ω+)||εα/2∂xq¯ε||L2(Ω+), (94) | Z 1 0 mv(y)(c0|x=0− τ ˆcf)ϕ|x=0 < v > −Pe0mτ ε2−α dy| ≤ C|c0|x=0− τ ˆcf| || p v(y)ϕ|x=0||L2(0,1) (95) Estimates (91)-(95) give a precise behavior of the right hand side in (90). We note that for α ≥ 1 one has 3α/2 − 2 ≥ α/2 − 1, and from (91)-(95)we get ||∂yqε||L2(Ω+)≤ C ½ ||c0||H1(Ω+)+ |c0|x=0− τ ˆcf|+ (1 + |τ |1/2ε1−α/2)||∂xc0||L2(Ω+) ¾ . (96)
Estimate (96) implies existence of a subsequence of {qε}, denoted by the
same superscript, and Q ∈ L2(Ω+), such that ∂
yqε * Q weakly in L2(Ω+).
Passing to the limit in the variational equation (90), yields the following equation for Q: Z Ω+ Q∂yϕ dxdy = − Z Ω+ (v(y)− < v >)∂xc0,trϕ dxdy, (97)
where c0,tr is the solution for the problem ½
τ c0,tr+ < v > ∂xc0,tr =< c0 > in Ω+;
c0,tr|x=0 = ˆcf. (98)
Next we obtain that
∂yqε= εα−2∂yˆc ε− c0
Pe0 * ∂yP4(y)(< c0> −τ c
weakly in L2(Ω+), for every τ ∈ C
+. This is in accordance with the results by Choquet and Mikeli´c from [12].
With c0(0) = cf(0) we use Lemma 1 and conclude that
εα−2∂yˆc ε− c0 Pe0 * ∂yP4(y)(< c0 > −τ c 0,tr) in H2(C +, L2(0, +∞)), (100) εα−2∂yc ε− cef f Pe0 * −∂yP4(y)∂tc tr in L2(R2 +). (101)
We would like to go one step forward, extend the results from [12] and use the hyperbolic effective equation to prove the weak convergence of qεto
P4(y)(< c0 > −τ c0,tr). STEP 3
Having in mind the estimates from STEP 2, we introduce the function wε by wε= ε α−2 Pe0(ˆc ε− c0) − P 4(y)(< c0> −τ c0) (102) and write the corresponding variational equation.
After inserting (102) into (90) and using the identity Z Ω+ v(y)− < v > Pe0 ∂xc 0ϕ dxdy + Z Ω+ ∂yP4 Pe0 < v > ∂xc 0∂ yϕ dxdy = 0
we get the following variational equation for wε:
1 τb(w ε, ¯ϕ) = − Z Ω+ P4(y)(< c0> −τ c0)ϕ dxdy− Z Ω+
(v(y)P4(y) − m)∂x(< cτ0>− c0)ϕ dxdy −ε
2(α−1) Pe0 Z Ω+ ∂xc 0 τ ∂xϕ dxdy − εα Pe0 Z Ω+ P4(y)∂x(< cτ0 >− c0)∂xϕ dxdy − Z 1 0 v(y)(P4(y)− m < v >)( < c0 > |x=0 τ − c 0| x=0)ϕ|x=0 dy + m Z Ω+ ∂x ¡ c0− < c0 > τ ¢ ∂yP4∂yϕ dxdy, ∀ ϕ ∈ H1(Ω+), ∀τ ∈ C+. (103)
Let us estimate the terms at the right hand side: | Z Ω+ P4(y)(< c0 > −τ c0)ϕ dxdy| ≤ C|| < c0 > −τ c0||L2(Ω+)||ϕ||L2(Ω+), (104) | Z Ω+(v(y)P4(y) − m)∂x( < c0 > τ − c 0)ϕ dxdy| ≤ Cε1−α/2 r < ³ 1 τ ´ ||∂x(< cτ0> − c0)||L2(Ω+)|| r <³ 1 τ ´ εα/2−1∂yϕ||L2(Ω+), (105) |ε 2(α−1) Pe0 Z Ω+∂x c0 τ ∂xϕ dxdy| ≤ C |τ | ε3α/2−2 r < ³ 1 τ ´ ||∂xc0||L2(Ω+)|| r <³ 1 τ ´ εα/2∂xϕ||L2(Ω+), (106) εα Pe0 | Z Ω+ P4(y)∂x(< c0 > τ − c 0)∂ xϕ dxdy| ≤ Cεα/2 r < ³ 1 τ ´ ||∂x(< cτ0>− c0)||L2(Ω+)|| r <³ 1 τ ´ εα/2∂xϕ||L2(Ω+), (107) | Z 1 0 v(y)(P4(y) − m < v >)( < c0> |x=0 τ − c 0| x=0)ϕ|x=0 dy| ≤ C |τ | r < ³ 1 τ ´ | < c0> |x=0− τ ˆcf| || r <³ 1 τ ´p v(y)ϕ|x=0||L2(0,1), (108) |m Z Ω+∂x ¡ − c0+< c0 > τ ) ¢ ∂yP4∂yϕ dxdy| ≤ Cε1−α/2 r < ³ 1 τ ´ ||∂x( < c0 > τ − c 0)|| L2(Ω+)|| r <³ 1 τ ´ εα/2−1∂yϕ||L2(Ω+) (109) Therefore, since 1 |τ | r < ³ 1 τ ´ ≤ √1<τ,
for α > 4/3, we have <³ 1 τb(w ε, wε)´= Z Ω+|w ε|2dxdy + εα−2<³ 1 τ ´ Z Ω+|∂yw ε|2dxdy+ εα<³ 1 τ ´ Z Ω+|∂xw ε|2dxdy + 1 2< ³ 1 τ ´ Z 1 0 |pv(y)wε|x=0|2 dy ≤ C ½ || < c0 > −τ c0||L2(Ω+)+ ε1−α/2||∂x(< c0> −τ c0)||L2(Ω+)+ εα/2||∂xc0||L2(Ω+)+ | < c0> |x=0− τ ˆcf| ¾2 (110) The estimate (110) gives
( ||∂ywε||L2(Ω+)≤ Cε1−α/2; ||wε||L2(Ω+)≤ C; ||∂xwε||L2(Ω+)≤ Cε−α/2; || √ vwε|x=0||L2(0,1) ≤ C. (111) Consequently, there is w = w(x, τ ) ∈ L2(R
+), for every τ ∈ C+ such that wε* w in L2(Ω+) and ∂ywε→ 0 in L2(Ω+), ∀τ ∈ C+. (112) Next we take the test function depending only on x, ϕ = ϕ(x) ∈ H1(R
+). Then we pass to the limit in the variation equation (103). Since ϕ does not depend on y and terms are either small or involve the section mean equal to zero, we obtain that the right hand side converges to zero when ε → 0. Then passing to the limit ε → 0 in the left side of (103) yields
Z +∞ 0 τ wϕ(x) dx − Z +∞ 0 < v > w∂xϕ(x) dx = 0, ∀ϕ ∈ H1(R+). (113) The equation (113) yields w ∈ H1(R
+) and w(0, τ ) = 0. Therefore w = 0 on R+ for all τ ∈ C+. This proves (28).
It remains to prove the convergence with respect to the time as well. Difficulty is that bounds in (111) depend on τ and their integrability is to be discussed.
We use the results of the Section 4.2. Using estimate (110), assumptions on the data and Lemmas 1 and 2, we obtain that
||wε||H2(C+;L2(Ω+))+ εα/2−1|| r <³ 1 τ ´ ∂ywε||H2(C+;L2(Ω+))≤ C. (114)
Now we repeat the above convergence argument but in H2(C
+; L2(Ω+)) and obtain (29). This proves the theorem. ¤
6
Proof of Theorem 2
STEP 1
We construct the corresponding boundary layer through the problem v(y)∂zβ = ∂yyβ in Ω+, (115)
β(0, y) = P4(y) −< v >m on (0, 1), (116) ∂yβ|y=0,1= 0 for x ∈ R+. (117) Since R01v(y)β(0, y) dy = 0, we can apply the elementary separation of variables for the heat equation and conclude β has an exponential decay in z, i.e. that there is λ0> 0 such that
|β(z, y)| ≤ Ce−λ0z, ∀(z, y) ∈ Ω+. (118) For more details on the spectral properties of the problem (116)-(117) we refer to [14], vol. 5, page 63.
STEP 2 Next we set βε(x, y) = β( x ε2−αPe 0 , y) and wε,f ull= ε α−2 Pe0(ˆc ε−c0)−P 4(y)(< c0> −τ c0)+βε(x, y)(< c0> |x=0−τ c0|x=0). (119) We make the corresponding replacement in (103) and get
1 τb(w ε,f ull, ¯ϕ) = − Z Ω+ P4(y)(< c0> −τ c0)ϕ dxdy + Z Ω+ βε(< c0 > |x=0− τ c0|x=0)ϕ dxdy + ε α Pe0 Z Ω+ (< c0> |x=0− τ c0|x=0)∂xβε∂xϕ dxdy− Z Ω+
(v(y)P4(y) − m)∂x(< cτ0>− c0)ϕ dxdy −ε
2(α−1) Pe0 Z Ω+ ∂xc 0 τ ∂xϕ dxdy − εα Pe0 Z Ω+ P4(y)∂x(< cτ0 >− c0)∂xϕ dxdy − Z 1 0 v(y)(P4(y)− m < v >)( < c0 > |x=0 τ − c 0| x=0)ϕ|x=0 dy + m Z Ω+ ∂x ¡ c0− < c0 > τ ¢ ∂yP4∂yϕ dxdy, ∀ ϕ ∈ H1(Ω+), ∀τ ∈ C+. (120)
Next we note the modifications in the estimate (104): | Z Ω+P4(y)(< c0> −τ c 0)ϕ dxdy| ≤ Cε1−α/2 r < ³ 1 τ ´ || < c0> −τ c0||L2(Ω+)|| r <³ 1 τ ´ εα/2−1∂yϕ||L2(Ω+), (121)
Furthermore we have two new terms: | Z Ω+ βε(< c0 > |x=0− τ c0|x=0)ϕ dxdy| ≤ C ε(2−α)/2| < c0> |x=0− τ c0|x=0|||ϕ||L2(Ω+) | Z Ω+ εα Pe0(< c0 > |x=0− τ c 0| x=0)∂xβε∂xϕ dxdy| ≤ Cεα−1| < c0 > |x=0− τ c0|x=0|||εα/2∂xϕ||L2(Ω+)
Now for α > 4/3, we get again
||wε||L2(Ω+) ≤ Cemin{3α/2−2,1−α/2} and wε→ 0 in L2(Ω+), ∀τ ∈ C+ (122)
and the (34) is proved.
It remains to prove (35). The only term which needs attention is Z
Ω+
P4(y)(< c0> −τ c0)ϕ dxdy.
Here we use Lemma 3 giving us < c0 > −τ c0→< c0 > −τ c0,trin H2(C+; L2(Ω+)), as ε → 0. Now we take as test function ϕ = ¯wε,f ull. The test function
con-verges weakly to zero in H2(C+; L2(Ω+)), as ε → 0. Therefore we have <(1
τb(w
ε,f ull, wε,f ull)) → 0, as ε → 0. This proves (35). ¤
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